1. Field of the Invention
The present invention relates generally to digital image processing. More specifically, the present invention relates to a method for reducing artifacts at object edges in halftone images.
2. Description of the Related Art
When printing images on an image forming device, discrete units of monochrome colorants (e.g., ink, toner) are placed onto a media sheet. Color imaging devices use halftone screens to combine a finite number of colors and produce, what appears to the human eye, many shades of colors. The halftone process converts different tones of an image into single-color dots of varying size and varying frequency. In general, halftone screens of as few as three colors may suffice to produce a substantial majority of visible colors and brightness levels. For many color imaging devices, these three colors comprise cyan, magenta, and yellow. In many cases, a fourth color, black, is added to deepen dark areas and increase contrast. In order to print the different color components in a four color process, it is necessary to separate the color layers, with each color layer converted into halftones. In monochrome printers, black halftones are used to represent varying shades of gray.
Before printing, the full color or grayscale images are converted into the requisite number of halftone images. This process entails a reduction in color depth. That is, the number of colors that are used to represent discrete units in an image is reduced from some relatively large value to one-bit per unit. As an example, a grayscale image comprising 256 shades of gray, may be converted from eight bits per pixel into a halftone image comprising one-bit per pixel (or smaller unit defined by a halftone screen). A general problem with the halftone operation is degradation in image quality. Various methods of reducing the image color depth are known, including “Nearest Color” and “Ordered Dither” techniques. “Error Diffusion” is another technique that is commonly used to scale down the image resolution. Error diffusion, as the name implies, works by locally distributing or diffusing known errors that result from the resolution change. In other words, the errors are diffused among a few pixels, which may produce a slight bleeding or fraying effect. This problem is particularly noticeable at distinct boundaries between light and dark regions in an original image.
The problem becomes even more pronounced when printing a scanned image. Scanning often produces blurred edges as a result of factors such as mechanical and optical limitations, sensor resolution, and quantization errors. Some scanners also implement anti-aliasing or image filtering to soften the edges of objects such as text. Thus, for devices such as All-In-One or Multifunction printers capable of direct copying, the edges of detailed objects may be distorted twice. First, the edges may be blurred by the scan process. Second, the blurred edges produced by the scanner may be frayed during the halftone process where the color depth is reduced for reproduction by single-color dots.
Some conventional techniques used to compensate for the blurred or frayed edges include spatial domain filtering or unsharp mask filters applied to the color or grayscale image prior to halftoning. However, these techniques may tend to reduce the size of objects as they work to enhance the contrast on both the light and dark sides of an object. Furthermore, these conventional techniques may not compensate for halftone artifacts such as the fraying of halftone edges.